In this talk, we will review the evolution of the computer technologies after the PC Era, including embedded systems, smart devices and smartphones, cloud computing, IoT, AI, and then AIoT & Edge Computing that are happening today, and discuss how the trends were developed.

1. From Embedded to IoT, and
From Cloud to Edge & AIoT
-- A computer technology trend review for the past 20 years
William Liang (梁文耀), Ph.D.
Technical Director / Chief Architect
Taipei Design Center, ADLINK
2020.03 1

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Technology Transition for the Last 20 years
This will gonna be kind of a storytelling session about what I saw and what I experienced for the past 20 years. :^)
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Technology Transition -- Embedded Systems
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● Personal computer technologies were
getting mature enough to be applied to
Embedded Systems, which in fact benefit
a lot from semiconductor and open source,
especially for SoC and Embedded Linux.
Embedded Systems
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Technology Transition -- Smart Devices (Smartphones)
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● Early participant in Android development
○ The 1st porting to Academic research
embedded platform
○ Extend Android to smart IoT applications
Smartphone and Smart Devices
https://www.youtube.com/watch?v=6A3n2u3SabA&feature=youtu.be
https://www.youtube.com/watch?v=11Z8r-eRJ7w&feature=youtu.be
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● HTML5 / Firefox OS
○ Cloud-based concept
○ Cross platform App development
○ With maximal number of developers
○ Suitable for devices with rich media,
such as smart TV
Toward Smart Appliances - Firefox OS
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Technology Transition -- Cloud Computing
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● Rich of computing and storage resources
● With the trend of high speed mobile network (4G/5G)
○ Low latency + High bandwidth
○ Potential to utilize grand cloud resource “locally”
● To integrate cloud storage to smart phones
○ HopeBay Tera: unlimited space, cloud-based phone
○ Cloud Memory Extension (CME) Technologies
○ Extend to Data-centric IoT
The Cloud Age
http://jerrydrussell.com/business-2/ibms-cloud-supercompute
r-powers-artificially-intelligent-consumer-apps/
https://www.openstack.org/software/
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Cloud-based Data-centric IoT
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Technology Transition -- IoT
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● IoT means
The mature IT technologies can
be applied to everywhere!
● IoT is based on:
○ Embedded HW/SW technologies
○ Communication technologies
○ Wireless Sensor Networks technologies
Arising of IoT
http://edition.cnn.com/2013/05/02/travel/london-city-airport-internet-of-things/
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IoT Applications (1/2)
http://www.greenpeak.com/Application/ResidentialApps.html
http://www.nexcom.com.tw/news/detail/digital-signage-responds-to-its-audience http://hunterkirk.livejournal.com/702857.html
https://ec.europa.eu/digital-agenda/en/
embedded-systems
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IoT Applications (2/2)
http://www.technologyreview.com/photogallery/4
27652/building-tesla/
https://www.tesla.com/sites/default/files/styles/customer_2
x_mobile_1200x816/public/media-vimeo/154227644.jpg
http://www.defenseindustrydaily.com/cv-ucavs-the-return-of-ucas-0
3557/
http://www.nasa.gov/mission_pages/msl/multim
edia/pia15090.html
http://www.forcesofgeek.com/2012/07/sdcc-exclusive-limited-i-robot-3d-blu.html
http://igyaan.in/2012/01/20344/autogyaan-mercedes-be
nz-futuristic-dice-dashboard-concept/
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IoT + Cloud
The Clouds
✓Any where & Any time
✓Storage & Computing
✓Availability & Reliability
✓Security
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A Typical IoT Structure
https://www.openstack.org/software/
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Successful Story: nextDrive Energy IoT
https://youtu.be/yEcUE1awTxU 17

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Smart Grid Applications
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Architecture Transformation in IoT Age
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Technology Transition -- Artificial Intelligence
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https://upload.wikimedia.org/wikipedia/commons/e/e3/BigData_2267x1146_trasparent.png
● Big data came from a lot of Small data!
● Traditional methods of prediction and modeling based on statistics
are changed drastically.
○ Sampling may not be a necessary thing because all data could be acquired
directly!
Big Data ⇒
Cognitive Computing ⇒
Artificial Intelligence (AI)
Big Data and AI
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Technology Transition -- AI + IoT ⇒ AIoT
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● IoT + Big Data ⇒ Analysis and AI
● AI is actually not a new technology. It's now
feasible because:
○ A lot of data can be obtained
○ High Performance Computing
● AI includes
○ Machine Learning (ML)
○ Deep Learning (DL)
Data Analytics and AI
http://www.scientificamerican.com/article.cfm?id
=yahoo-supercomputer-google-open-source
https://upload.wikimedia.org/wikipedia/zh/7/73/%E4%BA%BA%E5%B7
%A5%E6%99%BA%E6%85%A7_%E6%B5%B7%E5%A0%B12.jpg
© William Liang, http://csie.ntut.edu.tw/~wyliang
https://www.researchgate.net/figure/GPGPU-architecture-overview_fig1_276250251
Source: Intel Education Programhttps://en.wikipedia.org/wiki/Neural_network 23

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● AI/ML/DL Computation
○ AI Training
○ AI Inference
● Complexity of AI: O(n3
)~O(n5
)
● Big data makes “n” exploded!
● Cloud computing resources
increase in a relatively slower
manner
○ although high performance
computing techniques is getting
better and better...
○ Quantum computers?
Challenge: Computational Resources
https://www.bigocheatsheet.com/
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Technology Solution -- AIoT + Edge Computing
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● Edge: close to data generation places
● Data can be processed at the front edge side before being sent to
the cloud, to reduce the traffics
○ Useless-data filtering
○ Noise reduction
○ Preprocessing and computation
● AI Inference can also be done at
Edge side directly
○ Shorten inference latency
The Edge Computing Solution
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Cloud ⇒ Edge ⇒ IoT
The Clouds
✓Any where & Any time
✓Storage & Computing
✓Availability & Reliability
✓Security
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New Architecture with Edge Computing for IoT
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ADLINK Edge Computing and AIoT Solutions
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● Enables scalable, real-time, reliable, high performance and
interoperable data exchanges between publishers and subscribers
● Based on a set of standards managed by the Object Management
Group (OMG)
DDS - Data Distribution Service
https://www.researchgate.net/figure/Architecture-of-DDS_fig1_224372490
https://www.electronicdesign.com/industrial-automation/article/
21806104/adlink-delivers-opensource-dds-platform
Designed to address the needs of mission and business-critical
applications such as military command and control systems, air
traffic control, transportation management, modeling and
simulation, SCADA & utilities, and other big data applications.
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ROS2 - Robot OS
https://www.researchgate.net/figure/ROS1-ROS2-architecture-for-DDS-ap
proach-to-ROS-We-clarify-the-performance-of-the-data_fig1_309128426
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● ADLINK Technology is now part of the ROS 2
Technical Steering Committee (TSC) organized by
Open Robotics. Current ROS 2 TSC members
include:
○ ADLINK Technology
○ Amazon
○ Apex.AI
○ Arm
○ Bosch
○ Canonical
○ eProsima
○ Intel
○ LG Electronics
○ Microsoft
○ Open Robotics
○ ROBOTIS
○ Samsung
○ TARDEC
○ Tier IV
○ Toyota Research Institute
ADLINK Joins ROS 2 Technical Steering Committee
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● Computer Application Evolution
○ PC → Smart devices & Cloud → IoT
● Maturity of New Technologies
○ 5G & AI ⇒ AIoT
● Challenge of Cloud with IoT
○ Computational complexity of AI
○ Bandwidth of big data
● Edge computing
○ Data preprocessing
○ AI inferences
○ Realistic Business Values
● ADLINK Edge Solutions: DDS + ROS2 + AIoT
Conclusion
5 System Components for Smart Applications
● Cloud: data analysis and AI training
● Edge: data preprocessing and AI inference
● Terminal: user interface for
● IoT: communication and networking
● Sensors: information collection
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34. THANK YOU
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